A Knowledge-Modeling Approach to Integrate Multiple Clinical Practice Guidelines to Provide Evidence-Based Clinical Decision Support for Managing Comorbid Conditions

Clinical management of comorbidities is a challenge, especially in a clinical decision support setting, as it requires the safe and efficient reconciliation of multiple disease-specific clinical procedures to formulate a comorbid therapeutic plan that is both effective and safe for the patient. In this paper we pursue the integration of multiple disease-specific Clinical Practice Guidelines (CPG) in order to manage co-morbidities within a computerized Clinical Decision Support System (CDSS). We present a CPG integration framework-termed as COMET (Comorbidity Ontological Modeling & ExecuTion) that manifests a knowledge management approach to model, computerize and integrate multiple CPG to yield a comorbid CPG knowledge model that upon execution can provide evidence-based recommendations for handling comorbid patients. COMET exploits semantic web technologies to achieve (a) CPG knowledge synthesis to translate a paper-based CPG to disease-specific clinical pathways (CP) that include specialized co-morbidity management procedures based on input from domain experts; (b) CPG knowledge modeling to computerize the disease-specific CP using a Comorbidity CPG ontology; (c) CPG knowledge integration by aligning multiple ontologically-modeled CP to develop a unified comorbid CPG knowledge model; and (e) CPG knowledge execution using reasoning engines to derive CPG-mediated recommendations for managing patients with comorbidities. We present a web-accessible COMET CDSS that provides family physicians with CPG-mediated comorbidity decision support to manage Atrial Fibrillation and Chronic Heart Failure. We present our qualitative and quantitative analysis of the knowledge content and usability of COMET CDSS.